Report generated by the iraceplot package
Scenario
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## irace scenario:
scenarioFile = "D:/Users/SuperUser/OneDrive/mestrado/pesquisa/irace/cifar10-irace - exp7/irace/scenario.txt"
execDir = "D:/Users/SuperUser/OneDrive/mestrado/pesquisa/irace/cifar10-irace - exp7/irace"
parameterFile = "D:/Users/SuperUser/OneDrive/mestrado/pesquisa/irace/cifar10-irace - exp7/irace/parameters.txt"
forbiddenExps = list(<bytecode>, <bytecode>, <bytecode>, <bytecode>, <bytecode>, <bytecode>, <bytecode>, <bytecode>, <bytecode>, <bytecode>) = expression(neuroniosDensos1%%2 != 0, neuroniosDensos2%%2 != 0, (maxpooling1 + maxpooling2 + maxpooling3 + maxpooling4 + maxpooling5 + maxpooling6 + maxpooling7 + maxpooling8) > 4, tamanhoFiltros2%%2 == 0, tamanhoFiltros3%%2 == 0, tamanhoFiltros4%%2 == 0, tamanhoFiltros5%%2 == 0, tamanhoFiltros6%%2 == 0, tamanhoFiltros7%%2 == 0, tamanhoFiltros8%%2 == 0)
forbiddenFile = "D:/Users/SuperUser/OneDrive/mestrado/pesquisa/irace/cifar10-irace - exp7/irace/forbidden.txt"
initConfigurations = NULL
configurationsFile = ""
logFile = "D:/Users/SuperUser/OneDrive/mestrado/pesquisa/irace/cifar10-irace - exp7/irace/irace.Rdata"
recoveryFile = ""
instances = c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9")
trainInstancesDir = ""
trainInstancesFile = "D:/Users/SuperUser/OneDrive/mestrado/pesquisa/irace/cifar10-irace - exp7/irace/train-instances.txt"
sampleInstances = FALSE
testInstancesDir = ""
testInstancesFile = ""
testInstances = NULL
testNbElites = 1
testIterationElites = FALSE
testType = "t.none"
firstTest = 2
eachTest = 1
targetRunner = "D:/Users/SuperUser/OneDrive/mestrado/pesquisa/irace/cifar10-irace - exp7/irace/target-runner.bat"
targetRunnerLauncher = ""
targetRunnerLauncherArgs = "{targetRunner} {targetRunnerArgs}"
targetRunnerRetries = 5
targetRunnerData = ""
targetRunnerParallel = NULL
targetEvaluator = NULL
deterministic = TRUE
maxExperiments = 1000
maxTime = 0
budgetEstimation = 0.02
minMeasurableTime = 0.01
parallel = 2
loadBalancing = TRUE
mpi = FALSE
batchmode = "0"
digits = 2
quiet = FALSE
debugLevel = 0
seed = 123456
softRestart = TRUE
softRestartThreshold = 0.01
elitist = TRUE
elitistNewInstances = 1
elitistLimit = 2
repairConfiguration = NULL
capping = FALSE
cappingType = "median"
boundType = "candidate"
boundMax = NULL
boundDigits = 0
boundPar = 1
boundAsTimeout = TRUE
postselection = 0
aclib = FALSE
nbIterations = 0
nbExperimentsPerIteration = 0
minNbSurvival = 0
nbConfigurations = 0
mu = 5
confidence = 0.95
## end of irace scenarioParameters
| n_total | n_fixed | n_int | n_real | n_cat | n_ord | n_conditional | n_dependent |
|---|---|---|---|---|---|---|---|
| 38 | 0 | 37 | 1 | 0 | 0 | 30 | 0 |
Parameters tree
├─camadasConvolucionais │ ├─maxpooling2 │ ├─maxpooling3 │ ├─maxpooling4 │ ├─maxpooling5 │ ├─maxpooling6 │ ├─maxpooling7 │ ├─maxpooling8 │ ├─batchNormalization2 │ ├─batchNormalization3 │ ├─batchNormalization4 │ ├─batchNormalization5 │ ├─batchNormalization6 │ ├─batchNormalization7 │ ├─batchNormalization8 │ ├─numFiltrosInd2 │ ├─numFiltrosInd3 │ ├─numFiltrosInd4 │ ├─numFiltrosInd5 │ ├─numFiltrosInd6 │ ├─numFiltrosInd7 │ ├─numFiltrosInd8 │ ├─tamanhoFiltros2 │ ├─tamanhoFiltros3 │ ├─tamanhoFiltros4 │ ├─tamanhoFiltros5 │ ├─tamanhoFiltros6 │ ├─tamanhoFiltros7 │ └─tamanhoFiltros8 ├─maxpooling1 ├─batchNormalization1 ├─camadasDensas │ ├─neuroniosDensos1 │ └─neuroniosDensos2 ├─dropout ├─learningIndex ├─batchIndex └─numEpocas
Parameters file
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camadasConvolucionais "--nc=" i (1,8) maxpooling1 "--mp1=" i (0,1) maxpooling2 "--mp2=" i (0,1) | camadasConvolucionais > 1 maxpooling3 "--mp3=" i (0,1) | camadasConvolucionais > 2 maxpooling4 "--mp4=" i (0,1) | camadasConvolucionais > 3 maxpooling5 "--mp5=" i (0,1) | camadasConvolucionais > 4 maxpooling6 "--mp6=" i (0,1) | camadasConvolucionais > 5 maxpooling7 "--mp7=" i (0,1) | camadasConvolucionais > 6 maxpooling8 "--mp8=" i (0,1) | camadasConvolucionais > 7 batchNormalization1 "--bn1=" i (0,1) batchNormalization2 "--bn2=" i (0,1) | camadasConvolucionais > 1 batchNormalization3 "--bn3=" i (0,1) | camadasConvolucionais > 2 batchNormalization4 "--bn4=" i (0,1) | camadasConvolucionais > 3 batchNormalization5 "--bn5=" i (0,1) | camadasConvolucionais > 4 batchNormalization6 "--bn6=" i (0,1) | camadasConvolucionais > 5 batchNormalization7 "--bn7=" i (0,1) | camadasConvolucionais > 6 batchNormalization8 "--bn8=" i (0,1) | camadasConvolucionais > 7 numFiltrosInd2 "--nf2=" i (5,8) | camadasConvolucionais > 1 numFiltrosInd3 "--nf3=" i (5,8) | camadasConvolucionais > 2 numFiltrosInd4 "--nf4=" i (5,8) | camadasConvolucionais > 3 numFiltrosInd5 "--nf5=" i (5,8) | camadasConvolucionais > 4 numFiltrosInd6 "--nf6=" i (5,8) | camadasConvolucionais > 5 numFiltrosInd7 "--nf7=" i (5,8) | camadasConvolucionais > 6 numFiltrosInd8 "--nf8=" i (5,8) | camadasConvolucionais > 7 tamanhoFiltros2 "--tf2=" i (3,11) | camadasConvolucionais > 1 tamanhoFiltros3 "--tf3=" i (3,11) | camadasConvolucionais > 2 tamanhoFiltros4 "--tf4=" i (3,11) | camadasConvolucionais > 3 tamanhoFiltros5 "--tf5=" i (3,11) | camadasConvolucionais > 4 tamanhoFiltros6 "--tf6=" i (3,11) | camadasConvolucionais > 5 tamanhoFiltros7 "--tf7=" i (3,11) | camadasConvolucionais > 6 tamanhoFiltros8 "--tf8=" i (3,11) | camadasConvolucionais > 7 camadasDensas "--nd=" i (1,3) neuroniosDensos1 "--nd1=" i (4,128) | camadasDensas > 1 neuroniosDensos2 "--nd2=" i (4,128) | camadasDensas > 2 dropout "--dr=" r (0,0.5) learningIndex "--li=" i (0,5) batchIndex "--bti=" i (4,10) numEpocas "--ne=" i (10,300)
General information
- irace version: 3.5.6863679
- Iterations: 20
- Configurations: 466
- Instances: 10
- Experiments: 953
- Elite configurations: 4
- Soft restarts: 0
- Rejected configurations: 0
- Running time (seconds): 23 (CPU-user); 32 (CPU-sys); 367444 (Wall-clock)
- Termination reason: Not enough budget to race more than the minimum configurations
By iteration
By instance
Elite configurations
The final best configurations found by irace are:
Parallel coordinates visualization (only elites)
#> Warning in min(x): nenhum argumento não faltante para min; retornando Inf
#> Warning in max(x): nenhum argumento não faltante para max; retornando -Inf
#> Warning in min(data[, ".FITNESS."]): nenhum argumento não faltante para min; retornando Inf
#> Warning in max(data[, ".FITNESS."]): nenhum argumento não faltante para max; retornando -InfSampling model
The frequency of the parameter values sampled by irace:
#> Warning in min(x, na.rm = na.rm): nenhum argumento não faltante para min; retornando Inf
#> Warning in max(x, na.rm = na.rm): nenhum argumento não faltante para max; retornando -Inf
#> Warning in min(x, na.rm = na.rm): nenhum argumento não faltante para min; retornando Inf
#> Warning in max(x, na.rm = na.rm): nenhum argumento não faltante para max; retornando -Inf
#> Warning in min(x, na.rm = na.rm): nenhum argumento não faltante para min; retornando Inf
#> Warning in max(x, na.rm = na.rm): nenhum argumento não faltante para max; retornando -Inf
#> Warning in min(x, na.rm = na.rm): nenhum argumento não faltante para min; retornando Inf
#> Warning in max(x, na.rm = na.rm): nenhum argumento não faltante para max; retornando -Inf
#> Warning: Groups with fewer than two data points have been dropped.
#> Warning in max(ids, na.rm = TRUE): nenhum argumento não faltante para max; retornando -Inf
#> Warning: Groups with fewer than two data points have been dropped.
#> Warning in max(ids, na.rm = TRUE): nenhum argumento não faltante para max; retornando -Inf
#> Warning: Groups with fewer than two data points have been dropped.
#> Warning in max(ids, na.rm = TRUE): nenhum argumento não faltante para max; retornando -Inf
#> Warning: Groups with fewer than two data points have been dropped.
#> Warning in max(ids, na.rm = TRUE): nenhum argumento não faltante para max; retornando -Inf
Testing performance
- Number of elites tested: 1
- Iteration elites tested: FALSE
Performance of the elite configurations on the test instances
#> No test instances given.Final elite configurations on the test instances
#> No test instances given.Iteration elite configurations on the test instances
#> Iteration elites were not tested.